Xiang Xu

Xiang Xu

PhD Student

Simon Fraser University

About Me

I am a first-year PhD student at Simon Fraser University, advised by Yasutaka Furukawa. Previously, I graduated from Carnegie Mellon University with BS in Electrical & Computer Engineering, where I was advised by Kris Kitani.

I am interested in computer vision, deep learning and machine learning. My main research focus is understanding 3D structured geometry such as CAD, building, and articulated object.

Education
  • PhD in Computer Science, 2021 - Present

    Simon Fraser University

  • MS in Computer Science, 2019 - 2021

    Simon Fraser University

  • BS in ECE, 2014 - 2018

    Carnegie Mellon University

Experiences

Publications

See Google Scholar for full publications
SkexGen: Generating CAD Construction Sequences by Autoregressive VAE with Disentangled Codebooks

VQ-VAE with disentangled codebooks to generate diverse and high-quality CAD models, enhances user control, and enables efficient exploration of the design space.

Structured Outdoor Architecture Reconstruction by Exploration and Classification

A new explore-and-classify framework for structured architectural reconstruction from aerial image.

D3D-HOI: Dynamic 3D Human-Object Interactions from Videos

Monocular video dataset with ground truth annotations of 3D object pose, shape and part motion. We leverage 3D human pose for more accurate inference of the object spatial layout and dynamics.

MCMI: Multi-Cycle Image Translation with Mutual Information Constraints

Treat single-cycle image translation as modules that can be used recurrently where the process is bounded by mutual information constraints between the input and output images.

Error Correction Maximization for Deep Image Hashing

Use the Hamming bound to derive optimal criteria for learning hash codes with a deep network.